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Bind Dataset Version

bind_dataset_version

Bind the one frozen dataset version a fine-tuning project trains on (from list_dataset_versions). Permanent for the project: the same version again is a no-op, a different one is refused — open a new project to train on another version. Freezes nothing, trains nothing, spends nothing. Scope: write.

Input Schema

NameRequiredDescriptionDefault
datasetIdYesDataset ID the version belongs to
projectIdYesFine-tuning project ID from list_fine_tuning_projects
versionIdYesFrozen version ID from list_dataset_versions
customerIdNo(Converra superadmin only) Target customer ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (readOnlyHint=false, destructiveHint=false, openWorldHint=false), the description discloses irreversibility ('Permanent for the project'), idempotency semantics, the refusal mode for a conflicting version, and that the call has no side effects on freezing/training/spend. This is rich behavioral context the annotations alone do not carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four tight sentences, front-loaded with the core action (bind the frozen version), followed by persistence semantics, side-effect disclaimers, and scope. No filler and no repetition of schema content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no output schema, the description covers purpose, permanence, idempotency, refusal behavior, alternatives, and side-effect profile. An agent has everything needed to decide when and how to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all four parameters are already documented with their source tools (projectId, versionId). The description reinforces that versionId comes from list_dataset_versions but adds no new syntax, format, or constraint detail, and does not address the superadmin-only customerId. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (bind) and the exact resource (the one frozen dataset version a project trains on), and proactively contrasts with freeze_dataset_version by asserting 'Freezes nothing, trains nothing, spends nothing.' An agent can distinguish this from the freeze/list siblings without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly routes the agent to list_dataset_versions as the source of the version, states the when-not (a different version is refused), and names the alternative path ('open a new project to train on another version'). Repeat-call behavior (same version = no-op) is also spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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